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The influence of publication delays on three ISI indicators

Author

Listed:
  • Guang Yu

    (Library, Harbin Institute of Technology)

  • Rui Guo

    (School of Management, Harbin Institute of Technology)

  • Yi-Jun Li

    (School of Management, Harbin Institute of Technology)

Abstract

Summary Based on the transform function model of the observed citing process, the analytical expression of the age distribution of citations is deduced, and it is theoretically proved that the peak value of the citation distribution curve would fall and shift backward along with increasing the average publication delay and the peak age has a direct proportion relation with the pure delay and would be prolonged along with increasing the delay or decreasing the aging rate. The influence of the average publication delay on three ISI indicators impact factor, immediacy index and cited half-life are studied; in one subject discipline, the bigger the delay, the lower the three indicators of journals. Using the sensitivity theory, sensitivity formulae of the three indicators to publication delay parameters are deduced and it is found that responses of these indicators to changes of publication delays are different according to different time constant of the aging process; The faster the aging rate of a discipline literature is, the worse the influence of publication delays on the indicators of journals in the discipline.

Suggested Citation

  • Guang Yu & Rui Guo & Yi-Jun Li, 2006. "The influence of publication delays on three ISI indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 69(3), pages 511-527, December.
    • Handle: RePEc:spr:scient:v:69:y:2006:i:3:d:10.1007_s11192-006-0167-0
    DOI: 10.1007/s11192-006-0167-0
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    Citations

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    Cited by:

    1. Guijie Zhang & Guang Yu & Yuqiang Feng & Luning Liu & Zhenhua Yang, 2017. "Improving the publication delay model to characterize the patent granting process," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(2), pages 621-637, May.
    2. Jingda Ding & Dehui Du, 2023. "A study of the correlation between publication delays and measurement indicators of journal articles in the social network environment—based on online data in PLOS," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(3), pages 1711-1743, March.
    3. Guijie Zhang & Yuqiang Feng & Guang Yu & Luning Liu & Yanqiqi Hao, 2017. "Analyzing the time delay between scientific research and technology patents based on the citation distribution model," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1287-1306, June.
    4. Guang Yu & Yi-Jun Li, 2010. "Identification of referencing and citation processes of scientific journals based on the citation distribution model," Scientometrics, Springer;Akadémiai Kiadó, vol. 82(2), pages 249-261, February.
    5. Guang Yu & Yi-Jun Li, 2007. "Parameter identification of the observed citation distribution," Scientometrics, Springer;Akadémiai Kiadó, vol. 71(2), pages 339-348, May.
    6. Guang Yu & Ming-Yang Wang & Da-Ren Yu, 2010. "Characterizing knowledge diffusion of Nanoscience & Nanotechnology by citation analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(1), pages 81-97, July.
    7. Guang Yu & Liang Wang, 2007. "The self-cited rate of scientific journals and the manipulation of their impact factors," Scientometrics, Springer;Akadémiai Kiadó, vol. 73(3), pages 321-330, December.
    8. Hamid Bouabid, 2011. "Revisiting citation aging: a model for citation distribution and life-cycle prediction," Scientometrics, Springer;Akadémiai Kiadó, vol. 88(1), pages 199-211, July.

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